Interval-valued sensory evaluation for customized beverage product formulation and continuous manufacturing

Isaev, Svetlin; Jreissat, Mohannad; Makatsoris, Charalampos; Bachour, Khaled; McCulloch, Josie; Wagner, Christian

Abstract

Understanding of consumer preferences and perceptions is a vital challenge for the food and beverage industry. Food and beverage product development is a very complex process that deals with highly uncertain factors, including consumer perceptions and manufacturing complexity. Sensory evaluation is widely used in the food industry for product design and defining market segments. Here, we develop a two-step approach to minimize uncertainty in the food and beverage product development, including consumers as co-creators. First, we develop interval-valued questionnaires to capture sensory perceptions of consumers for the corresponding sensory attributes. The data captured is modelled with fuzzy sets in order to then facilitate the design of new consumer-tailored products. Then, we demonstrate the real-world manufacture of a personalized beverage product with a continuous food formulation system. Finally, we highlight consumers` perceptions for the corresponding sensory attributes and their fuzzy set generated agreement models to capture product acceptance for the formulated and commercial orange juice drinks, and consequently to establish that continuous beverage formulator is capable of making similar commercial products for individuals.

Citation

Isaev, S., Jreissat, M., Makatsoris, C., Bachour, K., McCulloch, J., & Wagner, C. (2017). Interval-valued sensory evaluation for customized beverage product formulation and continuous manufacturing.

• Conference Name: 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017)
• End Date: Jul 12, 2017
• Acceptance Date: Mar 14, 2017
• Publication Date: Jul 9, 2017
• Deposit Date: Apr 26, 2017
• Publicly Available Date: Jul 9, 2017
• Journal: Proceedings of the IEEE International Fuzzy Systems Conference
• Electronic ISSN: 1544-5615
• Peer Reviewed: Peer Reviewed
• Public URL: https://nottingham-repository.worktribe.com/output/871908
• Publisher URL: http://ieeexplore.ieee.org/document/8015695/
• Additional Information: Published in: 2017 IEEE International Conference on Fuzzy Systems. (FUZZ-IEEE), doi: 10.1109/FUZZ-IEEE.2017.8015695